1 citations · 1 across the 5 of their papers we have counts for
5 papers
LeanGRPO: Eliminating Redundant Recomputation in Diffusion RL
Sijie Wang, Zhiqiang Tan, Xinrui Yang +1
Diffusion reinforcement learning (RL) has recently achieved significant success in post-training image and video generative models. However, most diffusion RL methods, including Da…
LLM-Driven Kernel Evolution: Automating Driver Updates in Linux
Arina Kharlamova, Jiawen Liu, Tianyi Zhang +4
Linux kernel evolution breaks drivers through API/ABI changes, semantic shifts, and security-hardening updates. We introduce DRIVEBENCH, an executable corpus of kernel…
MInCo: Mitigating Information Conflicts in Distracted Visual Model-based Reinforcement Learning
Shiguang Sun, Hanbo Zhang, Zeyang Liu +4
Existing visual model-based reinforcement learning (MBRL) algorithms with observation reconstruction often suffer from information conflicts, making it difficult to learn compact r…
Grounded Answers for Multi-agent Decision-making Problem through Generative World Model
Zeyang Liu, Xinrui Yang, Shiguang Sun +4
Recent progress in generative models has stimulated significant innovations in many fields, such as image generation and chatbots. Despite their success, these models often produce…
Imagine, Initialize, and Explore: An Effective Exploration Method in Multi-Agent Reinforcement Learning
Zeyang Liu, Lipeng Wan, Xinrui Yang +3
Effective exploration is crucial to discovering optimal strategies for multi-agent reinforcement learning (MARL) in complex coordination tasks. Existing methods mainly utilize intr…